It looks to me as if that’s because you are treating them as if they are intended to be deductive inferences when in fact they are inductive ones.
At no point have I intended to argue that (e.g.) it is impossible that the results found in this study are the result of accurate rational evaluation by the faculty in question. Only that it is very unlikely. The fact that one can construct possible worlds where their behaviour is close to optimal is of rather little relevance to that.
Google did find that academic performance is no good predictor for job performance at Google.
Among people actually hired by Google. Who (1) pretty much all have very good academic performance (see e.g. this if it’s not clear why that’s relevant) and (2) will typically have been better in other respects if worse academically, in order to get hired: see e.g. this for more information.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
you argue as if scientific studies nearly always replicate
Not intentionally. I’m aware that they don’t. None the less, scientific studies are the best we have, and it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing.
None the less, scientific studies are the best we have
“Best we have” doesn’t justify a small confidence interval. If there no good evidence available on a topic the right thing to do is to be uncertain.
it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing
The default way to act in those situations is to form your opinions based on meta-analysis.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
You basically think that a bunch of highly paid staticians make a very trivial error when a lot of money is at stake. How confident are you in that prediction?
If there is no good evidence available on a topic the right thing to do is to be uncertain.
I agree. (Did I say something to suggest otherwise?)
The default way [...] is to form your opinions based on meta-analysis.
Given the time and inclination to do the meta-analysis (or someone else who’s already done the work), yes. Have you perchance done it or read the work of someone else who has?
I agree. (Did I say something to suggest otherwise?)
On this topic it seems like your position is that you know that employers act irrationally and don’t hire woman who would perform well.
My position is that I don’t know whether or not that’s a case. That means you have a smaller confidence interval. I consider the size of that interval unjustified.
Given the time and inclination to do the meta-analysis
In the absence of that work being done it’s not good to believe that one knows the answer.
My position is that I’ve seen an awful lot of evidence, both scientific and anecdotal, that seems best explained by supposing such irrationality. A few examples:
Another study of attitudes to hiring finding that for applicants early in their career just changing the name from female to male results in dramatically more positive assessment. (The differences were smaller with a candidate several years further into his/her career.)
A famous study by Goldberg submitted identical essays under male and female names and found that it got substantially better assessments with the male name. (I should add that this one seems to have been repeated several times, sometimes getting the same result and sometimes not. Different biases at different institutions?)
In each case, of course one can come up with explanations that don’t involve bias—as some commenters in this discussion have eagerly done. But it seems to me that the evidence is well past the point where denying the existence of sexist biases is one hell of a stretch.
It looks to me as if that’s because you are treating them as if they are intended to be deductive inferences when in fact they are inductive ones.
At no point have I intended to argue that (e.g.) it is impossible that the results found in this study are the result of accurate rational evaluation by the faculty in question. Only that it is very unlikely. The fact that one can construct possible worlds where their behaviour is close to optimal is of rather little relevance to that.
Among people actually hired by Google. Who (1) pretty much all have very good academic performance (see e.g. this if it’s not clear why that’s relevant) and (2) will typically have been better in other respects if worse academically, in order to get hired: see e.g. this for more information.
I conjecture that, ironically, if Google measure again, they’ll find that GPA became a better predictor of job success when they stopped using it as an important metric for selecting candidates.
Not intentionally. I’m aware that they don’t. None the less, scientific studies are the best we have, and it’s not like there’s a shortage of studies finding evidence of the sort of sex bias we’re discussing.
“Best we have” doesn’t justify a small confidence interval. If there no good evidence available on a topic the right thing to do is to be uncertain.
The default way to act in those situations is to form your opinions based on meta-analysis.
You basically think that a bunch of highly paid staticians make a very trivial error when a lot of money is at stake. How confident are you in that prediction?
I agree. (Did I say something to suggest otherwise?)
Given the time and inclination to do the meta-analysis (or someone else who’s already done the work), yes. Have you perchance done it or read the work of someone else who has?
Not very.
[EDITED to fix a punctuation typo]
On this topic it seems like your position is that you know that employers act irrationally and don’t hire woman who would perform well. My position is that I don’t know whether or not that’s a case. That means you have a smaller confidence interval. I consider the size of that interval unjustified.
In the absence of that work being done it’s not good to believe that one knows the answer.
My position is that I’ve seen an awful lot of evidence, both scientific and anecdotal, that seems best explained by supposing such irrationality. A few examples:
The study we’ve been discussing here.
A neurobiologist transitions from female to male and is immediately treated as much more competent.
Another study of attitudes to hiring finding that for applicants early in their career just changing the name from female to male results in dramatically more positive assessment. (The differences were smaller with a candidate several years further into his/her career.)
A famous study by Goldberg submitted identical essays under male and female names and found that it got substantially better assessments with the male name. (I should add that this one seems to have been repeated several times, sometimes getting the same result and sometimes not. Different biases at different institutions?)
Auditioning orchestral players behind a screen makes women do much better relative to men.
In each case, of course one can come up with explanations that don’t involve bias—as some commenters in this discussion have eagerly done. But it seems to me that the evidence is well past the point where denying the existence of sexist biases is one hell of a stretch.